Topic
Goal programming
About: Goal programming is a research topic. Over the lifetime, 4330 publications have been published within this topic receiving 117758 citations.
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01 Nov 1985
TL;DR: Introduction History and Applications Development of the LGP Model An Algorithm for Solution Algorithm Illustration Duality and Sensitivity Analysis Extensions
Abstract: Introduction History and Applications Development of the LGP Model An Algorithm for Solution Algorithm Illustration Duality and Sensitivity Analysis Extensions
202 citations
TL;DR: This paper demonstrates that the BFGA is effective by offering the possibility of searching over tens of thousands of plans for trade-off sets of non-dominated plans, and presents an application of the model to the Tongzhou Newtown in Beijing, China.
202 citations
TL;DR: This paper attempts to review the literature on the linear BLP problems and presents the basic models and the characterizations of the problem, the areas for application, the existing solution approaches, and the related models and areas for further research.
Abstract: Multi-level programming is characterized as mathematical programming to solve decentralized planning problems. The decision variables are partitioned among ordered levels. A decision-maker at one level of the hierarchy may have his own objective function and decision space, but may be influenced by other levels.
202 citations
TL;DR: An interactive fuzzy goal programming approach to determine the preferred compromise solution for the multi-objective transportation problem by focusing on minimizing the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function.
Abstract: This paper presents an interactive fuzzy goal programming approach to determine the preferred compromise solution for the multi-objective transportation problem. The proposed approach considers the imprecise nature of the input data by implementing the minimum operator and also assumes that each objective function has a fuzzy goal. The approach focuses on minimizing the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. The solution procedure controls the search direction via updating both the membership values and the aspiration levels. An important characteristic of the approach is that the decision maker's role is concentrated only in evaluating the efficient solution to limit the influences of his/her incomplete knowledge about the problem domain. In addition, the proposed approach can be applied to solve other multi-objective decision making problems. The performance of this solution approach is evaluated by comparing its results with that of the two existing methods in the literature.
200 citations
TL;DR: This study integrates the Taguchi loss function, analytical hierarchy process (AHP), and multi-choice goal programming (MCGP) model for solving the supplier selection problem and allows decision makers to set multiple aspiration levels for the decision criteria.
199 citations